|Over the last two decades, macroecology – the analysis of large-scale, multi-species ecological patterns and processes – has
established itself as a major line of biological research. Analyses of statistical links between environmental variables and
biotic responses have long and successfully been employed as a main approach, but new developments are due to be utilized.
Scanning the horizon of macroecology, we identifi ed four challenges that will probably play a major role in the future.
We support our claims by examples and bibliographic analyses. 1) Integrating the past into macroecological analyses, e.g.
by using paleontological or phylogenetic information or by applying methods from historical biogeography, will sharpen
our understanding of the underlying reasons for contemporary patterns. 2) Explicit consideration of the local processes
that lead to the observed larger-scale patterns is necessary to understand the fi ne-grain variability found in nature, and will
enable better prediction of future patterns (e.g. under environmental change conditions). 3) Macroecology is dependent on
large-scale, high quality data from a broad spectrum of taxa and regions. More available data sources need to be tapped and
new, small-grain large-extent data need to be collected. 4) Although macroecology already lead to mainstreaming cuttingedge
statistical analysis techniques, we fi nd that more sophisticated methods are needed to account for the biases inherent
to sampling at large scale. Bayesian methods may be particularly suitable to address these challenges. To continue the vigorous
development of the macroecological research agenda, it is time to address these challenges and to avoid becoming too
complacent with current achievements.|